34 results about "Matrix method" patented technology

Disclosed in the present invention are a method and apparatus for synthesizing spatially cross-correlated multi-point ground motions fitting a response spectrum. The method comprises: using an influence matrix method to obtain ground motion acceleration time histories fitting a target reaction spectrum with high precision, and calculating a Fourier amplitude spectrum and a phase spectrum thereof; and considering a calculation relationship between a power spectral density function and the Fourier amplitude spectrum, taking the power spectral density function of the obtained time histories as an initial value, using a random vibration theory and Cholesky decomposition to obtain spatially cross-correlated multi-point ground motion time histories, further taking into account a phase spectrum of the ground motion time histories fitting the target reaction spectrum with high precision, and performing correction and iteration to obtain spatially cross-correlated multi-point ground motions fitting a response spectrum. The present invention overcomes the shortcomings in current multi-point ground motion time history synthesis techniques, such as the difficulty in ensuring good fitting to a target response spectrum and the non-stationarity of synthesized ground motions, helping to improve the reliability of dynamic response analysis results for large-scale engineering structures under the action of multi-point ground motions.

The present invention provides a comprehensive evaluation method for multiple performance indicators, comprising: a data collection step: obtaining multiple single performance indicator data during operation in an application system, wherein the multiple single performance indicators include response time, startup time, throughput, error rate and resource utilization rate; a data processing step: performing standardization processing on the single performance indicator data to obtain standardized scores of the single performance indicators; a weight allocation step: assigning corresponding first weights to the single performance indicators based on a hierarchical analysis method; a weight adjustment step: adjusting the first weights based on an adjustment judgment matrix method to obtain final weights; a score calculation step: performing weighted calculation based on the standardized scores of the single performance indicators and the final weights to obtain a comprehensive score of the performance indicators; and a score output step: querying a preset score level based on the comprehensive score of the performance indicators, and outputting the corresponding application system performance evaluation result.

The invention relates to a mobile robot control method and system based on fault prediction, and the system comprises a multi-mode inverse kinematics solver which dynamically selects a solving mode according to the condition number of a Jacobian matrix, and carries out the solving of the Jacobian matrix according to the condition number from small to large; respectively selecting a transpose matrix method, a damping least square method and constrained quadratic programming to calculate the joint angle adjustment amount to adapt to bad working conditions such as singular configuration; the self-adaptive integral controller is used for independently adjusting position / attitude ring gain through a decoupling gain matrix, dynamically inhibiting vibration and reducing steady-state errors in combination with errors and fault indexes; and the fault prediction and reconstruction subsystem calculates a joint fault index in real time, and the index integrates torque deviation, temperature, harmonic distortion, vibration and wear data and implements hierarchical response. According to the system, the singular region stability is remarkably improved, the decoupling performance and the fault response speed are controlled, and the secondary fault risk is reduced.

The invention discloses a non-uniform sparse sampling single-section near-field test system and method, and belongs to the technical field of test. According to the method, the single-section radiation field is expressed in a matrix form, the unknown transmission coefficient is solved from the system of linear equations through an inverse matrix method, and the defect that a traditional single-section near-field test method based on fast Fourier transform depends on the distribution uniformity of near-field samples is overcome; under the assumption that antenna transmission coefficients have sparsity, a compressed sensing technology is introduced, L1 norm minimization constraint is applied to a transmission coefficient vector q to ensure the sparsity, and under the condition that the number M of single-section near-field samples is smaller than the number J of unknown coefficients, the transmission coefficients can be solved from an underdetermined linear equation set; according to the invention, a non-uniform sampling-based single-section near-field test method is realized, and the flexibility of a sampling mode is improved; the number of sampling points and the scanning time are reduced, and the testing efficiency is improved; and the far-field reconstruction precision is higher.

The invention provides a tool geometric parameter optimization design method and system based on integrated simulation and a storage medium, and relates to the technical field of tool geometric parameter optimization design. Orthogonal experiment design is combined with parametric modeling, tool geometric parameter combination space is fully covered, and invalid exploration is reduced; establishing a nonlinear relation model by using support vector regression, and accurately mapping parameter and performance association; based on a dynamic weight distribution mechanism of an entropy method and a judgment matrix method, the rough machining cost reduction requirement and the finish machining high-quality requirement are met; an improved simulated annealing algorithm introduces a dynamic cooling strategy and global solution test, global search and local convergence capabilities are balanced, and premature convergence is avoided; and through modeling-simulation-optimization closed-loop iteration, automatic parameter updating and feedback verification are realized, and the design period is remarkably shortened. Therefore, while the machining quality is guaranteed, the tool loss and the trial and error cost are greatly reduced, and a high-stability and high-economical-efficiency solution is provided for machining of complex materials.

The invention relates to the technical field of power distribution network fault positioning, in particular to a power distribution network fault self-healing method based on fault detection positioning and isolation recovery. Comprising the steps of collecting data; judging that a fault occurs, and judging a fault type based on a wavelet transform method; screening candidate fault branches based on a matrix method, and obtaining fault distances of the candidate fault branches based on a traveling wave distance measurement method; on the basis of topological connection of candidate fault branches, a minimum set of switches needing to be disconnected is generated, the minimum power failure range is calculated, and the isolation priority is dynamically adjusted; and constructing a physical constraint of recovery operation and a multi-objective function of power supply recovery, solving the multi-objective function of power supply recovery, obtaining an interconnection switch state, a section switch state and a distributed power supply output adjustment instruction, and executing a power supply recovery action. According to the method, the strategy transparency and the operation and maintenance efficiency are improved, the problem of positioning failure of a traditional method under noise interference and multi-branch scenes is solved, and the fault positioning precision is improved.

The invention discloses a multi-probe spherical near-field sampling system based on compressed sensing and a test method, and belongs to the technical field of measurement. According to the method, the antenna transmission equation is expressed in a matrix form, the unknown transmission coefficient is solved from the linear equation set through the matrix method, and the defect that a traditional spherical near-field test method based on FFT depends on the distribution uniformity of near-field samples is overcome; according to the method, under the assumption that antenna transmission coefficients have sparsity, a compressed sensing technology is introduced, L1 norm minimization constraint is applied to a transmission coefficient vector q to ensure the sparsity of the transmission coefficient vector q, and under the condition that the number M of spherical near-field samples is smaller than the number J of unknown coefficients, the transmission coefficients can be solved from an underdetermined linear equation set; according to the invention, on the basis of sampling coordinates obtained based on prior information of an antenna, in combination with an adaptive positioning algorithm, each probe is controlled to autonomously select an optimal path and move to a specified position along an annular frame to carry out interference-free sampling, so that data acquisition of a pitching section at any angle is realized.

The invention discloses a near-field dynamics matrix-free finite element method based on a partial assembly strategy, and the method comprises the steps: decomposing a finite element stiffness matrix into a continuous product of a plurality of operators based on near-field dynamics operator decomposition; the element stiffness matrix is implicitly expressed as a function of a plurality of parameters, real-time calculation and reduction are carried out when needed, and partial assembly of the element stiffness matrix is achieved; and performing iterative solution on the partially assembled element stiffness matrix, directly calculating the element stiffness matrix and the element vector in the iterative solution process, and accumulating the calculation result back to the global degree of freedom. According to the method, a matrix-free method is used for replacing a traditional strategy based on an assembled matrix, and finite element numerical simulation of the near-field dynamic model is achieved.

The present application relates to the technical field of power system operation analysis and regulation, and specifically discloses a kind of VSC-HVDC system power flow regulation capability evaluation method, comprising the following steps: S1, the power flow regulation range mathematical model of establishing containing back-to-back flexible HVDC transmission system BTB;S2, establish new energy output uncertainty model;S3, construct power flow over-limit risk and risk adaptive power regulation mechanism;S4, generalized polynomial chaos matrix method is used to evaluate the two-way power flow regulation range;S5, output power flow regulation range evaluation results and visual index.The present application uses the above-mentioned VSC-HVDC system power flow regulation capability evaluation method, realizes the collaborative quantification of new energy randomness, operation risk and BTB regulation capacity, improves the accuracy and engineering practicability of the evaluation results, and provides a decision basis for power system planning and design, operation control.

This invention relates to a collaboratively driven method and system for identifying and calculating failure paths in hydraulic engineering systems. The method includes acquiring multi-source measured information and determining the statistical characteristics of random variables; constructing a finite element model based on these characteristics; generating pairs of random variables using a stochastic method, obtaining the structural response of the hydraulic structure under different random variable settings through finite element simulation, and calculating event reliability based on the structural response; identifying failure paths and modes based on the event reliability results using an improved branch-and-bound method, fitting the response surface function for each failure mode, and calculating the system failure probability based on the response surface function; considering the correlation between various failure modes, calculating the overall system failure probability using a matrix method. This invention integrates multi-source measured information, constructs a finite element model, identifies failure paths based on event reliability, and calculates failure probabilities by comprehensively considering various failure modes, making the failure probability closely resemble real-world operating conditions and enhancing the accuracy and comprehensiveness of the calculation.

The present invention provides a modular implementation method for obtaining the characteristic frequencies of a complex water conveyance system, including the following steps: S1: Decompose the complex water conveyance system into independent simple elements, where the simple elements include elastic pipeline elements, rigid pipeline elements, impedance elements, surge chamber elements, reservoir elements, oscillating valve elements, and turbine elements; S2: Sequentially number the simple elements and the nodes adjacent to the simple elements; S3: Sequentially compile the simple elements after the decomposition of the complex water conveyance system into sub-matrix expressions; S4: Construct the total matrix of the water conveyance system; S5: Determine the excitation input node and the response output node; S6: Solve the total matrix of the water conveyance system to determine the frequency response characteristics of the system. The present invention is based on the structural matrix method, models each hydraulic element in blocks, and the matrix form of the constructed elements does not change due to the change in the layout of the water conveyance system, with a high degree of modularity.

The invention discloses a co-excitation Wheatstone full-bridge circuit fault positioning method based on resistance measurement, and belongs to the technical field of flight load spectrum testing. The system comprises a graphical interface module, a measurement data management module, a circuit topology storage module, an admittance matrix calculation module, a fault diagnosis engine module, a result display module and a file management module. The implementation method comprises the following steps: constructing a topological structure of a co-excitation Wheatstone full-bridge circuit, and defining nodes, resistors and a connection relation; inputting a resistance value among the eight fixed measurement points; generating possible fault resistance combination constraints; calculating a theoretical equivalent resistance value through an admittance matrix method; calculating the error between the theoretical value and the measured value; preferentially processing infinite constraints, and searching an optimal fault combination; and outputting a fault resistor positioning position and a diagnosis report. According to the invention, through automatic calculation and an intelligent optimization algorithm, rapid and accurate fault positioning is realized, and the maintenance cost and time of a flight load spectrum test system are substantially reduced.

The present invention belongs to the technical field related to spatial error compensation of five-axis CNC machine tools. It discloses a real-time compensation method and device for the spatial attitude and position errors of a five-axis CNC machine tool. The method comprises the following steps: S1, establishing a spatial error model of the CNC machine tool; S2, separating and extracting the rotation error term from the comprehensive error term, and solving the compensation instruction for the rotation error term by obtaining a pseudo-inverse matrix method to obtain a compensation instruction for the attitude error; S3, separating the singular part and the non-singular part of the compensation value of the attitude error, replacing the ordinary inverse of the singular part parameter with a damped inverse, thereby obtaining a new attitude error compensation instruction and performing compensation; S4, subtracting the linear part of the translation axis error caused by the attitude error compensation from the linear part of the comprehensive error in the initial tool coordinate system, i.e., the translation axis error compensation instruction, and performing compensation. The present invention not only greatly improves computational efficiency, but also can better compensate for the tool attitude error of the machine tool.

The present invention discloses a flexible mechanism modeling method integrating kinematics and static and dynamic analysis methods, including the establishment of rigid body (with or without extension) units and flexible unit extension transfer matrices, the establishment of the overall transfer matrix / equation of the flexible mechanism, and the post-processing of the transfer matrix / equation results, which provides a new idea for solving the motion and mechanical characteristics of the flexible mechanism. When solving the characteristics of the flexible mechanism, the present invention establishes the kinematics, statics, and dynamic analysis equations of the mechanism in the same formula, which greatly simplifies the analysis process of the flexible mechanism, and is simpler and more intuitive than the overall flexibility matrix method, kinematic principle, and Lagrangian method. In addition, the mathematical model established by the present invention is not only applicable to the situation where the mechanism unit is subjected to force, but also applicable to the situation under the direct extension and deformation of the rigid body (such as the direct displacement change of the moving pair), and has strong versatility.

The invention provides an intelligent scheduling method for a job shop, and relates to the technical field of production scheduling, and the method comprises the following steps: constructing a resource availability matrix which is used for representing whether a processing procedure is allowed to use corresponding processing resources or not based on a job condition; constructing a resource strategy fingerprint used for representing a preset processing resource scheduling strategy for the processing procedure and the processing resource; according to a preset scheduling mode, synthesizing the resource availability matrix and the resource strategy fingerprint to generate an assignable parameter matrix; and inputting the assignable parameter matrix as a resource available set, constructing a scheduling optimization model and solving the scheduling optimization model in combination with a preset constraint condition and an optimization target of the job shop, and generating an intelligent scheduling scheme. According to the method, the resource availability matrix and the resource strategy fingerprints are independently constructed, the resource availability matrix and the resource strategy fingerprints are synthesized, an assignable parameter matrix method is obtained, decoupling of resource allocation and strategies is achieved, and therefore the flexibility, reproducibility and high efficiency of job shop scheduling are achieved.

The invention relates to the field of machine learning and pattern recognition, and particularly discloses a variance-covariance subspace distance-based multi-kernel subspace clustering method, which comprises the following steps of: S1, acquiring a high-dimensional data matrix, calculating a variance-covariance matrix and second-order statistical information thereof, defining a preliminary VCSD kernel value and obtaining a VCSD kernel matrix through exponential transformation and normalization, constructing a multi-core pool of r base cores; s2, constructing an optimized objective function based on non-negative matrix factorization, and solving to obtain a local affinity feature map of a block diagonal structure under constraint conditions; s3, capturing high-order feature association through a matrix method, and converting tensor optimization into matrix operation; s4, solving the target function by adopting an alternating optimization strategy, reducing the calculation complexity, and generating a target affinity graph; and S5, clustering the target affinity spectrum, and outputting a result. According to the technical scheme provided by the invention, the problems of missing statistical characteristics, complex calculation and nuclear noise interference of the existing method are solved, and the clustering precision and efficiency are effectively improved.

The application discloses a water engineering scheduling runoff intelligent simulation method, comprising: edge distribution function fitting: using the matrix method to calculate the mean, dispersion coefficient and skewness coefficient, and adopting a P-III type curve to construct a daily runoff frequency curve; wisdom knowledge set construction: using a time series model to establish wisdom knowledge sets of each parameter in a mixed Copula set, using a cooperative search algorithm, taking the minimum of the Akaike information criterion of the theoretical distribution and the empirical distribution as the target, and calibrating the wisdom knowledge set parameters; daily runoff simulation: based on the Bayesian rule, a mixed conditional Copula set is established, and Latin hypercube sampling is used to generate a long sequence of daily runoff. The method reduces the difficulty of daily runoff simulation by the mixed Copula, reduces the number of parameters, improves the fitting precision of the mixed Copula, speeds up the construction speed of the mixed Copula set, and provides a valuable technical tool for basin management.

The invention discloses a power system state estimation Hessian matrix method based on optimal control, and belongs to the technical field of power system state estimation. According to the method, a node power equation for state estimation of the alternating-current power distribution network is established, and a Jacobian matrix and a Hessian matrix of node power unbalance to node voltage and phase angle are deduced; a state estimation optimization model with the minimum sum of squares of node power measurement errors as a target is constructed, the power system state estimation Hessian matrix method based on optimal control is provided, the state estimation convergence is improved, meanwhile, the calculation speed is guaranteed, and compared with a traditional Newton-Raphson state estimation method, the method has the advantages that the calculation speed is improved, and the calculation efficiency is improved. The state estimation method is few in iteration times and good in convergence.

The invention discloses an intelligent numerical simulation and evaluation system based on a homotopy matrix method and RAG enhancement. The intelligent numerical simulation and evaluation system is used for high-precision simulation and evaluation of the water outlet process of a pipe folding unmanned aerial vehicle. According to the method, a multi-body system dynamic model is constructed through a homotopy matrix method, and intelligent construction, parameter optimization and multi-physics field coupling solution of a numerical pool can be realized in combination with a computational fluid mechanics (CFD) solver OpenFOAM and RAG technology. According to the method, the problems of complex modeling, low calculation efficiency and insufficient parameter optimization of a traditional method are solved, and efficient simulation and real-time evaluation of the water outlet process of the pipe folding unmanned aerial vehicle are achieved.

The invention discloses a production load balance control system and a control method thereof, belongs to the technical field of production scheduling, and is used for solving the problem of unbalanced scheduling load of multi-variety and small-batch products, the control system comprises a top layer module, a middle layer module and a bottom layer module, and the three modules can communicate information with one another; the top layer module is used for inputting and analyzing an order, and converting an order load to a frequency domain through a Fourier load smoothing algorithm; the middle layer module is used for arranging the optimal order sequence, arranging the optimal order sequence of the orders by adopting a three-dimensional evaluation matrix method on the premise of ORR optimal rule sorting, and generating an order delivery sequence; and the bottom layer module is used for dispatching of a job shop layer and issuing order tasks generated by the top layer module and the middle module to each job device. According to the invention, the problem of excessive production scheduling is inhibited from the source, and the balance of the load of the whole chain from order receiving to delivery to dispatching is realized through a layered ladder control architecture.

The invention discloses a probabilistic optimal power flow calculation method based on differential evolution and a discrete Fourier matrix, which efficiently processes the uncertainty of new energy output and load by coupling the probabilistic sampling capability of a discrete Fourier matrix method and a differential evolution optimization framework. According to the method, a discrete cosine transform matrix (DCTM) sub-method in DFTM is utilized to generate sample points, and the sample size is reduced to m + 1 from 2m + 1 of a traditional unscented transform (UT) method. The probabilistic optimal power flow problem of the island micro-grid containing high-proportion renewable energy sources can be efficiently and accurately solved, and meanwhile, the adaptability to asymmetrically distributed random variables is ensured.

The application discloses a kind of based on finite difference reduction multibody system transfer matrix method of rotating beam system dynamic characteristic analysis method and system.Method includes: the physical parameter model of rotating beam system is established, and the structural parameter of rotating beam is acquired;Rotating beam system dynamics control differential equation is established;Rotating beam system is discretized using finite difference method;The transfer matrix of the discretized multibody system model is constructed, and the transfer matrix is processed using reduction equation, and the reduced difference point reduction transfer matrix recursive relationship is obtained;The reduced state vector recursive equation is established, and the dynamic characteristic parameter of rotating beam system is calculated and output.The application is combined with finite difference method by multibody system transfer matrix method, and rotating beam element is discretized difference, and the differential term of rotating beam differential equation is differentially approximated to deduce transfer matrix, retains the characteristics of low matrix order involved in transfer matrix method, reduces the calculation scale, improves the success rate of numerical calculation result, and can effectively solve rotating beam and other dynamics problems.

The invention discloses a method for analyzing the machining precision of a machine tool by bolt performance degradation in consideration of hole position errors, which considers the influence of manufacturing hole position errors on the rigidity of a bolted part for the first time. The method comprises the following steps: firstly, extracting normal and tangential contact rigidities of a joint surface under the conditions of different hole position errors, fractal parameters and pre-tightening forces by utilizing an abaqus finite element method to obtain a data set; and then, taking the hole position error, the fractal parameter and the pre-tightening force as input vectors, taking the joint surface rigidity as an output vector, and training data by utilizing a BP neural network to complete rigidity prediction. And finally, establishing a dynamic model of the gantry machine tool based on a multi-body system transfer matrix method so as to explore the influence of performance degradation of the bolts on the machining precision of the machine tool, and providing technical guidance for optimization of the bolt joint surfaces in engineering.

The invention provides an expected function safety three-dimensional risk scene analysis method and system, a product and a vehicle, and relates to the technical field of intelligent driving. According to the method, function cases, potential triggering conditions and potential function insufficiency are systematically integrated, a HAZOP method is used for recognizing hazardous behaviors and associating vehicle hazards, and the risk of the vehicle is analyzed. The risk acceptability is judged by combining severity and controllability evaluation, and then a matrix method is adopted to establish an association relationship among potential insufficient functions, risk hazard behaviors and potential trigger conditions, and a comprehensive risk score is calculated; and finally, constructing a complete risk scene model containing three dimensions including the scene containing the trigger condition, the trigger condition and the hazard scene, and realizing priority ranking of the risk scene according to the comprehensive score. According to the method, the systematicness, integrity and quantification degree of SOTIF analysis are effectively improved.

The present invention relates to a hypersurface positioning method and device based on nonlinear framework dictionary learning, aiming to solve the technical problem that the sparse representation and dictionary learning problems existing in the prior art are based on linear modeling, and the positioning problem cannot be fitted most efficiently by linear modeling, resulting in a decrease in positioning accuracy. The present invention includes: obtaining the positioning data of the training target in the target area with a label matrix; combining the label matrix method and the dictionary learning method to construct a dictionary learning model and a target classification model, and adding a nonlinear function based on the combination of the dictionary learning model and the target classification model to calculate the discriminant dictionary of the positioning data and the classification parameters in the target area; based on the discriminant dictionary, using a sparse coding method to obtain the sparse coefficients of the target to be located; based on the sparse coefficients, combined with the classification parameters, the position information of the target to be located is obtained.

The application discloses a kind of shipboard aircraft dynamics fast calculation method.Method includes following process: establishing shipboard aircraft catapult take-off multi-flexible body system dynamics model, establishes shipboard aircraft catapult take-off multi-flexible body system topology, utilize finite element method to establish main tire refinement finite element model, then tire flexible body dynamics characteristic parameter is exported and deduces the dynamics equation of tire flexible element, based on multi-body system transfer matrix method (MSTMM) and finite element modal synthesis method deduce shipboard aircraft catapult take-off multi-flexible body system total transfer equation and total transfer matrix, solve the inherent frequency of shipboard aircraft multi-flexible body system considering inflatable flexible tire and the dynamic response of catapult take-off;The method proposed in the application overcomes the defects of high matrix order and large amount of calculation of traditional methods when dealing with complex coupling system of shipboard aircraft containing inflatable flexible tire, has the advantages of fast calculation speed, high degree of programming and strong universality, provides an efficient calculation method for the dynamic analysis of complex shipboard aircraft multi-flexible body system.

The invention relates to a cooperative drive hydraulic construction system failure path identification and calculation method and system, and the method comprises the steps: obtaining multi-source actual measurement information, and determining the statistical characteristics of random variables; constructing a finite element model according to the statistical characteristics of the random variables; a random variable set pair is generated by adopting a random method, structural response quantities of the hydraulic structure under different random variable settings are obtained through finite element simulation, and event reliability is calculated according to the structural response quantities; identifying failure paths and modes according to an event reliability result by adopting an improved branch and bound method, fitting to obtain a response surface function of each failure mode, and calculating a system failure probability based on the response surface functions; and considering the correlation of each failure mode, and calculating the overall failure probability of the system through a matrix method. According to the method, the multi-source actual measurement information is integrated, the finite element model is constructed, the failure path is identified based on the event reliability, and the failure probability is calculated by overall planning of the failure modes, so that the failure probability fits the real working condition, and the accuracy and comprehensiveness of calculation are enhanced.

The application discloses a kind of deep submicron device working condition failure mechanism proportion calculation method based on matrix method, comprising the following steps: step one: determine the kind of failure mechanism existing in the deep submicron device to be measured, establish the acceleration model of each failure mechanism;Step two: calculate acceleration factor matrix AF;Step three: calculate relative acceleration factor vector B according to the acceleration test data;Step four: construct failure mechanism proportion solving equation set;Step five: solve the value range of relative factor RF;Step six: determine the proportion of four kinds of failure mechanisms under the working condition of the deep submicron device to be measured;Through the above steps, the contribution proportion of the failure mechanism existing in deep submicron device under any working condition to device degradation can be calculated in combination with acceleration test data.

The present invention discloses a method for locating disturbances in a distributed power grid based on an improved high-frequency energy method and a matrix method. The method comprises the following steps: decomposing and reconstructing disturbance data to obtain high-frequency power and high-frequency energy; determining the relative direction between the disturbance source and the monitoring point by using an improved high-frequency energy method directional criterion; forming a directional discrimination information matrix and a system structure information matrix, establishing a particle swarm optimization model, and limiting the particle swarm search motion space and particle motion span; constructing an evaluation function that is tolerant to directional discrimination information and is suitable for power grids containing distributed energy; and utilizing a particle swarm algorithm for iterative search to determine the optimal particle based on the evaluation function to accurately locate the disturbance source. By combining the improved high-frequency energy method directional criterion with an optimization matrix, the present invention improves the accuracy of locating power quality disturbance sources in power grids containing distributed energy.